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MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets

Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and u...

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Autores principales: Jurtz, Vanessa Isabell, Villarroel, Julia, Lund, Ole, Voldby Larsen, Mette, Nielsen, Morten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5042410/
https://www.ncbi.nlm.nih.gov/pubmed/27684958
http://dx.doi.org/10.1371/journal.pone.0163111
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author Jurtz, Vanessa Isabell
Villarroel, Julia
Lund, Ole
Voldby Larsen, Mette
Nielsen, Morten
author_facet Jurtz, Vanessa Isabell
Villarroel, Julia
Lund, Ole
Voldby Larsen, Mette
Nielsen, Morten
author_sort Jurtz, Vanessa Isabell
collection PubMed
description Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder.
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spelling pubmed-50424102016-10-27 MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets Jurtz, Vanessa Isabell Villarroel, Julia Lund, Ole Voldby Larsen, Mette Nielsen, Morten PLoS One Research Article Bacteriophages are the most abundant biological entity on the planet, but at the same time do not account for much of the genetic material isolated from most environments due to their small genome sizes. They also show great genetic diversity and mosaic genomes making it challenging to analyze and understand them. Here we present MetaPhinder, a method to identify assembled genomic fragments (i.e.contigs) of phage origin in metagenomic data sets. The method is based on a comparison to a database of whole genome bacteriophage sequences, integrating hits to multiple genomes to accomodate for the mosaic genome structure of many bacteriophages. The method is demonstrated to out-perform both BLAST methods based on single hits and methods based on k-mer comparisons. MetaPhinder is available as a web service at the Center for Genomic Epidemiology https://cge.cbs.dtu.dk/services/MetaPhinder/, while the source code can be downloaded from https://bitbucket.org/genomicepidemiology/metaphinder or https://github.com/vanessajurtz/MetaPhinder. Public Library of Science 2016-09-29 /pmc/articles/PMC5042410/ /pubmed/27684958 http://dx.doi.org/10.1371/journal.pone.0163111 Text en © 2016 Jurtz et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Jurtz, Vanessa Isabell
Villarroel, Julia
Lund, Ole
Voldby Larsen, Mette
Nielsen, Morten
MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets
title MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets
title_full MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets
title_fullStr MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets
title_full_unstemmed MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets
title_short MetaPhinder—Identifying Bacteriophage Sequences in Metagenomic Data Sets
title_sort metaphinder—identifying bacteriophage sequences in metagenomic data sets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5042410/
https://www.ncbi.nlm.nih.gov/pubmed/27684958
http://dx.doi.org/10.1371/journal.pone.0163111
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